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Microsoft officially announced the release of a new device-side small language model (SLM), Mu, specifically designed for the settings application in Windows 11 to create an intelligent AI agent. This marks a significant breakthrough in localized AI technology within operating system interactions. As a compact and efficient model, Mu runs through deep optimization on the neural processing unit (NPU), providing users with a low-latency, high-privacy natural language interaction experience. AIbase has compiled the highlights and industry impact of Mu, taking you on a journey to explore its features. Mu: Designed Specifically for Windows Settings

Recently, Volc Engine officially announced the launch of the enterprise AI mid-platform HiAgent 2.0, aiming to address real-world business needs and pain points in the development of Agent applications, helping enterprises achieve efficient delivery of intelligent bodies from development to operations. HiAgent 2.0 is positioned as an enterprise AI mid-platform, and compared to its predecessor HiAgent 1.0, it has expanded in four dimensions of functionality. Upwardly, HiAgent 2.0 provides more industry scenario templates and a rich plugin market, significantly lowering the barrier to building intelligent bodies; towards

Comprehensive analysis of the functional features and user experience of the LLM SEO Monitor tool, learn how to enhance brand visibility in AI search engines like ChatGPT and Gemini through professional monitoring, and gain commercial value from AI search traffic.

Recently, an open-source RAG (Retrieval-Augmented Generation) engine called RAGFlow has attracted significant attention in the industry. This enterprise-level AI tool, based on deep document understanding, provides companies with a brand-new solution for processing complex documents and achieving precise question answering through its powerful multimodal data processing capabilities and efficient workflows. RAGFlow: The Pioneer of Deep Document Understanding RAGFlow is a fully open-source RAG engine that focuses on deep document understanding, aiming to help businesses and individuals extract valuable information from massive amounts of unstructured data.

Recently, at the 2025 Volcano Engine FORCE Original Power Conference, Volcano Engine officially launched the intelligent solution platform for large models — PromptPilot. With the rapid development of AI technology reshaping various industries, how to effectively ask questions has become a key challenge for the implementation of large models. Different models have differences in understanding questions, and writing high-quality prompts is time-consuming and labor-intensive while requiring a high level of user experience.

At the recently held 'Force Primordial Power Conference', ByteDance’s Volcano Engine officially launched the DouBao large model 1.6 and video generation model Seedance 1.0pro. This release marks another leap forward in AI technology, particularly in multi-modal understanding and video generation, demonstrating strong market competitiveness. DouBao 1.6 has performed excellently in multiple international authoritative evaluations, especially excelling in complex reasoning and competition-level mathematics tests. Tan Dai, President of Volcano Engine, stated that this model not only supports multi-

At the FORCE Original Power Conference, Volcano Engine officially launched BeanPod Large Model 1.6 and its new video generation model Seedance 1.0 Pro, marking a comprehensive upgrade of AI cloud-native full-stack services. As a leading family of multimodal, high-value models, BeanPod Large Model 1.6 has undergone significant improvements in functionality and performance. ByteDance CEO Liang Ruobo stated at the launch event that BeanPod Large Model 1.6 adopts a unified pricing model, creating an input length-based pricing approach.

At the Volcano Force Original Power Conference held today, Tan Dai, president of Volcano Engine, disclosed a set of eye-catching data: By the end of May 2025, the daily average token calls of the BeanPod large model had reached 16.4 trillion, which is 137 times that at the time of launch. Tan Dai stated that since its release, the BeanPod large model has continued to iterate and optimize, being widely used in various scenarios such as content creation, intelligent customer service, data analysis, and others, becoming an important engine for enterprise intelligence transformation. According to the latest market data from IDC, Volcano Engine now holds *

At the recently held Bloomberg Technology Summit, Aravind Srinivas, CEO of Perplexity, revealed that in May 2023, the query volume of the Perplexity AI search engine reached an impressive 780 million times, and the platform's monthly user growth rate exceeded 20%. Srinivas said: "If we can maintain this growth rate, we expect the weekly query volume to reach one billion within a year." This is really impressive, as in just twenty...

Volcano Engine officially released its large model ecosystem square - MCP Servers. The launch of this innovative platform marks the entry of AI development into a brand-new modular assembly era. Through the deep collaboration of "MCP Market (Tool Square) + Volcano Ark (Large Model Service) + Trace (Application Development Environment)", MCP Servers has achieved a full-chain development closed loop from tool invocation, model inference to application deployment, greatly simplifying the development process and allowing developers to build A more efficiently.